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Shout-It-Now: Utilizing innovative technology to enhance mobile HIV counseling, testing and linkage-to-care in South Africa.

Authors: Joseph Daniels, PhD1, Arnošt Komárek, PhD2, Bruce Forgrieve, MBA3, Kathryn Pahl, PhD3, Stephen Stafford, BA3, Laurie Campbell Bruns, MPH1, Thomas Coates, PhD1


  1. Center for World Health, David Geffen School of Medicine, UCLA, USA
  2. Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic
  3. Shout-It-Now, Cape Town, South Africa


Background: Mobile HIV counseling and testing (HCT) increases uptake by hard-to-reach and infrequent testers like men and adolescents in South Africa. There is limited understanding of effective mobile HCT programs utilizing tools like technology and telephonic linkage to care counseling to increase HIV testing and linkage-to-care rates. We examine data from the Shout-it-Now (S-N) program that uses such tools in South Africa.

Methods: S-N utilizes various forms of technology and ongoing telephonic counseling within a six-step program of HIV testing and linkage-to-care support, and program data was analyzed over an 18-month period. Summative statistics was conducted on participant registration, HIV risk assessment, HIV testing and linkage-to-care profiles. HIV prevalence and linkage-to-care estimates were calculated using the Clopper Pearson method.

Results: S-N tripled the number of participants who completed HIV testing compared to similar mobile HCT programs. There were 72,220 participants who completed the program with 40% of participants being men at each site. There were 3343 participants who tested HIV-positive, and there were higher proportions of women who tested HIV-positive. Among the HIV-positive participants, 1335 opted into the telephonic linkage-to-care support program, and there was a 72.95% linkage-to-care mean rate.

Interpretation: Integrating technology, edutainment and ongoing telephonic support increased HIV testing rates, HIV case detection, and linkage-to-care rates compared to similar HCT models while improving the referral and support system for linkage-to-care. S-N is highly efficient and offers a cost-effective model for a large scale up of community-based HCT services.

Author contributions:

All authors conceived and designed the study. BF, KP, and SS acquired the data. JD, AK, TC, SS, KP and BF analyzed and interpreted the data. JD drafted the manuscript. JD, TC, SS, KP, AK critically revised and approved the final manuscript. BF, KP and SS obtained the funding.

Role of Funding Source:

Shout-It-Now was funded via CDC COAG: 1U2GGH000285, “Strengthening Prevention in South Africa through Innovative Mobile HCT”.  The funding source had no role in: study design to include the collection, analysis and interpretation of data; writing the manuscript; and submitting it for publication.

Ethics Committee Approval:

The Shout-It-Now program received ethical approval from CDC/PEPFAR Office of the Associate Director for Science. Participants provided consent for HCT electronically via the S-N system.


Research in Context:

Evidence before this study

We searched PubMed for studies and meta-analysis conducted to understand the effectiveness of community-based HIV counseling and testing (HCT) interventions in sub-Saharan African contexts, with a particular focus on mobile HCT interventions with linkage-to-care data. We selected studies conducted in a single country context and multi-country contexts; sample sizes varied depending on the scale of intervention. Search criteria included HCT and sub-Saharan Africa, men, women, adolescents, youth, South Africa; Project Accept; mobile HCT; community-based HCT; and mobile HCT and linkage-to-care.

Added value of this study

This study of one mobile HCT model updates a meta-analysis of community-based HCT. As a technology-driven mobile HCT model, Shout-It-Now demonstrates significantly higher number of testers and linkage-to-care rates than comparable models.

Implications of all the available evidence

Mobile HCT can expand testing beyond the number of testers measured in current programs, if technology and culturally appropriate entertainment are utilized. Mobile HCT can provide linkage-to-care support with the adaptation of technology and then demonstrate outcomes in this area.


The HIV epidemic remains generalized in South Africa with a sustained national HIV prevalence rate of 12.6% across all age ranges and 25% HIV prevalence among those 25-49 year old. More than 6.4 million South Africans are living with HIV/AIDS and many engage in behaviors that put them at risk of infecting others. While South Africa has demonstrated increased uptake of HIV counseling and testing (HCT) through both clinic and community centered initiatives, some estimate that as many as 50% of HIV positive people remain undiagnosed with continued needs to increase and diversify testing options.[1-6] To complement clinic-based testing initiatives, South Africa needs scalable and sustainable community-based HCT (CBHCT) models that foster routine testing habits and overcome the linkage-to-care challenges common among many CBHCT models.[7] The World Health Organization has recommended increasing the diversity of CBHCT models that work in conjunction with clinic-based HCT.[8] Common CBHCT models proven to increase HCT access include stand-alone centers and mobile units that serve venues such as shopping centers, transportation hubs, workplaces and schools.[9] Studies examining mobile HCT have shown increased uptake among first-time testers, men and youth who are reluctant to test in a clinic.[10-15] Mobile testing has also been proven to access larger numbers of individuals in both urban and rural settings, and can be cost-effective and acceptable with high quality service and accessibility.[1, 16, 17]

Current CBHCT models provide health education, counseling and testing services in tents or vans at community locations on a rotating basis.[18] People testing HIV-positive are subsequently referred to local clinics for HIV care. These models demonstrate high participation but have limited methods for tracking individuals from testing to linkage-to-care as few mobile HCT studies and programs that utilize technology to deliver participant education and track testing habits and linkage-to-care status. The challenge of linking HIV-positive clients diagnosed via CBHCT services to clinical care is well documented with some studies reporting 14% linkage-to-care rates by mobile CBHCT units.[3] Even referrals from hospitals to health centers have demonstrated a high attrition rate.[19] Among the key factors that have been found to impede linkage-to-care are participant economic barriers for clinic travel and poor administrative links between CBHCT sites and clinics.[20-22] Some CBHCT providers have sought to improve linkage-to-care by building referral relationships between themselves and clinics and by using approaches like referral letters and home visits to confirm linkage-to-care.[23, 24] However, these approaches have not effectively in addressed the mobile HIV testing and linkage-to-care gap.

We present the Shout-it-Now (S-N) program of mobile CBHCT, which utilizes a mix of client-centered services and technology to increase CBHCT scalability, acceptability and accountability. S-N differs from most mobile HCT providers in that it uses process-driven procedures supported by technology. We analyzed data collected over 18 months of S-N implementation (January 2012-June 2013) to assess: 1) HIV testing rates and 2) linkage-to-care rates. We discuss how S-N improves on the current mobile CBHCT model for deployment at a larger scale to successfully engage clients who don’t access HCT in clinical settings.



The S-N program combines technology (i.e. biometrics, video edutainment, telephonic linkage-to-care counseling) with culturally competent HCT services and a software system that seamlessly supports staff and clients through every step of the S-N process from registration to linkage to care. Technology is utilized to streamline organizational processes, educate participants, and support participants through each step of the program. The cost per participant is $17, and this is comparable to similar mobile HCT models and lower than stand-alone HCT.[5, 25]

Sites and Participant Recruitment. S-N operated two 14-person mobile teams in two South African districts: Tshwane district (an urban area including the City of Pretoria, population 2.9 million) in Gauteng province and Capricorn district (a rural area, population 1.3 million) in Limpopo province. The teams set up in shopping centers, markets, and central business districts, utilizing a prescribed operations protocol. Eight to ten counselor tents (3X3 meters) were pitched in a horseshoe formation. At the entrance were two additional tents, one for registration and one for a computer lab where participants watched S-N’s educational/risk assessment video on laptops. S-N sites were made highly visible, with colorful banners, music playing through a public announcement system, and S-N staff engaged passersby about the program and invited them to participate. Participants were 15-49 years of age and not asked about their previous testing history or HIV status.

Shout-it-Now Model. Six sequential steps form the S-N HCT program and are explained below. The first five steps were conducted during the HCT encounter at the mobile site and the final sixth step was conducted telephonically for up to seven weeks after a HIV-positive diagnosis via a centralized call center. For every client, each step was tracked using technology and the result of each step was automatically collected for program monitoring and evaluation via S-N’s integrated software program.

  1. Biometric Registration. The registration process begins with fingerprint registration that links clients anonymously and confidentially to a profile they build as they progress through the six-step S-N process. Once their fingerprint is registered, they are issued a unique identifier printed on a wristband that they then wear to track progression through the S-N process. Participants then complete a brief online demographic profile including socio-economic measures, cultural and racial identity, date of birth, and language. S-N’s use of biometric technology is supported by studies demonstrating that such technology is feasible and acceptable in low-resource settings and has been shown to be a significant factor in the engagement of participants in HIV testing and counseling and linkage-to-care.[24-26]


  1. HIV Edutainment. Online social networking, gaming, edutainment and telenovelas have been successfully used to deliver health knowledge, education and messaging.[27-32] S-N’s HIV education content is delivered by a 13-minute edutainment video viewed by each client on a personal laptop. The video features young South African celebrities (sports stars, musicians, designers and TV personalities), animation, dance and docudrama to teach clients about HIV risk, testing, disease development and living healthy with HIV. In the video, messages addressing both men’s and women’s HIV risk factors were delivered by men and women in order to create an inclusive educational experience.[7]


  1. Online Risk Assessment and Culturally Competent Pre-test Counseling. Embedded in the educational video was a set of HIV risk assessment questions. Participants were informed that questions about their health behaviors and opinions would appear during the video and that by answering these questions, they could improve the relevance and quality of their counseling session. The HIV risk assessment questions addressed sexual risk, TB and STI history, medical history, lifestyle, physical health, and medical male circumcision. The video ran automatically and was available in all local languages with counselors assisting participants who had low literacy levels. At the end of the video, clients were asked if they would like to consent for an HIV test.


Once a client consented to HIV testing, participants met privately with a counselor trained in key population cultural competence in a tent for pre-test counseling and testing. Counselors reviewed risk assessment profiles with their clients and then assessed their level of comprehension of educational content. The online risk assessments helped counselors tailor their HIV risk reduction messaging to each client’s needs. When pre-test counseling was completed, counselors asked the participant again if they consented to HIV testing. If participants declined testing, the counselor tried to motivate the client to accept testing by addressing the reasons for refusal but if the client could not be convinced to test, they exited the program at this point. Participants consenting to HIV testing were then tested.


  1. HIV testing. Counselors administered rapid HIV testing using kits certified by the South African National Department of Health and supplied by the respective provincial Departments of Health. There were two steps in the S-N testing process. First, a counselor collected a specimen using the test kit, which was linked to the client by a sticker bearing their unique identifier already stored in the S-N database. Participants were then escorted to a waiting area with activities and music videos while the test was processed. Second, the test kit and specimen were delivered to a dedicated staff member who read the HIV test result (the S-N database time stamped all test kits to protect against HIV test results being read too early or too late) and recorded the result in the S-N database by scanning the barcode on the test kit and inputting the result.


  1. Post-HIV test results counseling. The S-N database notified counselors on their laptops when their clients’ results were accessible via the client’s electronic record. At that time, counselors called clients back to their tent to deliver results and post-test counseling using a script specific to the client’s HIV result.


HIV-Negative Results: Counselors followed a 3-step procedure: 1) deliver the result and ascertain accurate comprehension of the result; 2) encourage routine HIV testing; 3) summarize the participant’s risk profile and help them devise a prevention plan to minimize their HIV risk.

HIV-Positive Results: Counselors followed a multi-step procedure: 1) deliver the preliminary test result and ascertain accurate comprehension of the result; 2) administer a different rapid HIV test to confirm results; 3) address individual concerns and questions; and 4) confirm results of second test. If the second test was negative, participants were referred to a clinic for a laboratory confirmation test. If the second test was positive, the counselor proceeded with a second set of steps:  1) deliver the HIV-positive diagnosis in a clear unambiguous way; 2) check for understanding of the result; 3) allow for emotional response; 4) assess participant’s support system; 5) discuss disclosure; 6) emphasize importance of accessing HIV care (including the importance of CD4 testing); and 7) discuss prevention options. After these steps were completed, individuals testing HIV-positive were provided a referral letter to a local clinic for follow-up care and were encouraged to participate in S-N’s ongoing linkage-to-care Call Center service.


  1. Telephonic Linkage-to-care Support Program. Participants opting to receive ongoing linkage-to-care services were provided free telephonic support from care coordinators at the S-N Call Center. Care coordinators had training in linkage-to-care counseling and were fluent in all South African languages. Within 48 hours of an HIV-positive diagnosis, a care coordinator called the client and commenced the process of motivating them to link to HIV care. Care coordinators used the participant’s e-profile stored in the S-N database to inform the telephonic support they provided to the participant until they linked to HIV care. Generally this support was provided up to seven weeks. Documentation of linkage to care was from the clients’ self report and was verified by descriptions of clinic-delivered CD4 results or enrollment in ART or in wellness programs.


Data analysis. Quantitative data from participant registration, HIV risk assessment, HIV testing and linkage-to-care profiles was analyzed to generate summative statistics using R software.[26] For HIV prevalence and linkage-to-care estimates, binomial confidence intervals were calculated using the Clopper Pearson method.



HIV Testing Engagement. A total of 72,220 individuals participated in Shout-It-Now across the two districts from June 2012-June 2013 (Table I) with an average completion time of 30 minutes per participant. There were higher numbers of women than men who completed the S-N program though the representation of men was over 40% in each site. The highest representation of participants by age was the 20-29 age group at 56.47% in Gauteng and 59.08% in Limpopo. Participant representation decreased sequentially from the 30-39, 15-19 and 40-49 age groups.

HIV Case Findings. In Table II, HIV prevalence rates by sex and age is shown along with confidence intervals. In this analysis of data collected over one year, the S-N program identified 3343 HIV-positive participants at 4.6% HIV prevalence. The HIV prevalence rates among testers in S-N were higher among women who were 30 years of age or older compared to men. In this age range, the HIV prevalence rate for women was 8.5-13.0% across the sites whereas it was 5.6-6.9% for men in the same age categories. The HIV prevalence rate range for both men and women from 15-29 years of age was 0.6-5.3% with 2.38% as the average rate. Most S-N participants tested HIV-negative across the sites, and the confidence intervals remained small for HIV testing based on gender alone with no distinct HIV prevalence rate differences between the two sites.

Linkage-to-Care. The distribution of those who opted into the linkage-to-care (LTC) support program by sex and age are represented in Table III. Out of the 3343 participants who tested HIV-positive through S-N, 1335 (39.93%) opted into the LTC program with the highest representation by women between the ages of 20-39 years. Participants who declined LTC support were either already in HIV care, lost to follow-up due to change in contact information, or not interested in being referred for care. Of those participating in the LTC program, 974 participants linked to care within seven weeks of completing the program. The range of linkage-to-care rates for adult men and women in both Gauteng and Limpopo are over 25.0-95.56% with a 72.95% mean rate for linkage-to-care, Table IV. Men and women in Limpopo had the lower linkage-to-care rates compared to Gauteng participants with the lowest rates among adolescent men (25.00%) and men over 40 years of age (35.59%). Otherwise, there was no distinctive difference in linkage-to-care rates between men and women across the sites in each age range over 20 years old.



The findings from the Shout-It-Now (S-N) program demonstrate exceptionally high HIV testing rates and above-average linkage-to-care rates among underserved communities including men and youth who are less likely to test.[1, 2, 4, 24] This HCT model nearly tripled the average number of participants compared to similar models over an 18-month period and maintained a high representation of both men and women including adolescents 15-17 years of age.[18] Further, the linkage-to-care rates for S-N maintain a mean of 72%, which is 58% higher of any reported model using a referral mechanism.[23]

High numbers of HIV-testers and HIV-cases detected. There was a 4.6% mean HIV prevalence across age, sex and site among testers in the S-N model with rates for women comparable to their national prevalence in South Africa.[2] Although the mean HIV prevalence is lower than the national prevalence, the number of HIV testers in S-N per site was significantly higher than comparable clinic-based testing methods and other mobile models.[17, 27] Further, HIV testing rates for men was less than women in S-N but high compared to national rates. This finding supports studies that show mobile testing increases the numbers of men in HCT and knowing their results within a context where 17% of men have ever tested for HIV.[1] With high numbers of HIV testers, the number of HIV-positive cases detected was high in S-N as well, such as 20-39 year old women with nearly double the number of cases detected compared to clinics.[17]

Improved linkage-to-care rates with referral support. Single method referral mechanisms like referral letters to HIV clinics used by many community-based HCT providers have demonstrated an average 14% linkage-to-care rate.[18] Utilizing a multi-method approach that included client-focused post-test counseling, referral letters to local clinics and ongoing telephonic support, there was a 72% mean linkage-to-care rate for men and women who participated in the LTC program through S-N. The S-N e-profile that participants developed when they completed the mobile HCT increased participant tracking efficiency, and this allowed care coordinators to engage participants in tailored telephonic linkage-to-care counseling. Further, there is increased need to develop novel and engaging approaches to address late presentation for HIV treatment in clinics.[1, 10] S-N demonstrated that multi-method approach that included telephonic support leads to higher rates of linkage-to-care, which has not been shown to our knowledge especially for those hard to reach like men and adolescents.[28-30]

S-N program addresses mobile HCT gaps. Technology allows mobile HIV testing programs to build voluntary participant tracking and support mechanisms from HCT to HIV care, which has been a challenge to implement and demonstrate outcomes.[4, 23] We show how technology allows participants to build an S-N e-profile as they proceed through the program steps. This e-profile gives the program data to provide tailored HIV testing and support for linkage-to-care, and participants may choose to retain their profiles if they plan to test with the program at a later date. These findings suggest that S-N engaged participants by using technology and educational media, which resulted in nearly triple the number of testers compared to any reported mobile model.[31-34] Technology applications used by S-N demonstrated high numbers along the continuum of care, and this technology was easily adaptable to urban and rural areas with high HIV prevalence and low numbers of testers.[2, 4]



Scaling up affordable HCT models that effectively engage large numbers of people to learn their HIV status and then efficiently link them to clinical care is a key priority in the global AIDS response. A highly organized service delivery process, use of multiple technologies to engage clients in education and track their HIV testing progression, risk profiles and test results can improve the effectiveness and scalability of HCT programs. We show how the Shout-It-Now (S-N) program is cost-effective compared to similar mobile HCT programs and addresses the test-and-linkage-to-care gap in many mobile HCT models. S-N is highly efficient and offers a cost-effective model for a large scale up of community-based HCT services.



The Shout-It-Now program received ethical approval from CDC/PEPFAR Office of the Associate Director for Science. Participants provided consent for HCT electronically via the S-N system.


Conflict of Interest:

Authors state that there are no conflicts of interest.



  1. van Rooyen H, McGrath N, Chirowodza A, Joseph P, Fiamma A, Gray G, et al. Mobile VCT: reaching men and young people in urban and rural South African pilot studies (NIMH Project Accept, HPTN 043). AIDS Behav 2013,17:2946-2953.
  2. Govindasamy D, Kranzer K, Ford N. Strengthening the HIV cascade to ensure an effective future ART response in sub-Saharan Africa. Trans R Soc Trop Med Hyg 2014,108:1-3.
  3. Govindasamy D, Meghij J, Kebede Negussi E, Clare Baggaley R, Ford N, Kranzer K. Interventions to improve or facilitate linkage to or retention in pre-ART (HIV) care and initiation of ART in low- and middle-income settings–a systematic review. J Int AIDS Soc 2014,17:19032.
  4. Govindasamy D, van Schaik N, Kranzer K, Wood R, Mathews C, Bekker LG. Linkage to HIV care from a mobile testing unit in South Africa by different CD4 count strata. J Acquir Immune Defic Syndr 2011,58:344-352.
  5. Grabbe KL, Menzies N, Taegtmeyer M, Emukule G, Angala P, Mwega I, et al. Increasing access to HIV counseling and testing through mobile services in Kenya: strategies, utilization, and cost-effectiveness. J Acquir Immune Defic Syndr 2010,54:317-323.
  6. Kranzer K, van Schaik N, Karmue U, Middelkoop K, Sebastian E, Lawn SD, et al. High prevalence of self-reported undiagnosed HIV despite high coverage of HIV testing: a cross-sectional population based sero-survey in South Africa. PLoS One 2011,6:e25244.
  7. Nachega JB, Uthman OA, del Rio C, Mugavero MJ, Rees H, Mills EJ. Addressing the Achilles’ heel in the HIV care continuum for the success of a test-and-treat strategy to achieve an AIDS-free generation. Clin Infect Dis 2014,59 Suppl 1:S21-27.
  8. Organization WH. Service delivery approaches to HIV testing and couseling (HTC): A strategic HTC programme framework. In. Geneva, Switzerland; 2012.
  9. van Schaik N, Kranzer K, Wood R, Bekker LG. Earlier HIV diagnosis–are mobile services the answer? S Afr Med J 2010,100:671-674.
  10. Hensen B, Taoka S, Lewis JJ, Weiss HA, Hargreaves J. Systematic review of strategies to increase men’s HIV-testing in sub-Saharan Africa. AIDS 2014.
  11. Hutchinson PL, Mahlalela X. Utilization of voluntary counseling and testing services in the Eastern Cape, South Africa. AIDS Care 2006,18:446-455.
  12. Maughan-Brown B, Nyblade L. Different dimensions of HIV-related stigma may have opposite effects on hiv testing: evidence among young men and women in South Africa. AIDS Behav 2014,18:958-965.
  13. Peltzer K, Matseke G, Mzolo T, Majaja M. Determinants of knowledge of HIV status in South Africa: results from a population-based HIV survey. BMC Public Health 2009,9:174.
  14. Tabana H, Doherty T, Swanevelder S, Lombard C, Jackson D, Zembe W, et al. Knowledge of HIV status prior to a community HIV counseling and testing intervention in a rural district of south Africa: results of a community based survey. BMC Infect Dis 2012,12:73.
  15. Venkatesh KK, Madiba P, De Bruyn G, Lurie MN, Coates TJ, Gray GE. Who gets tested for HIV in a South African urban township? Implications for test and treat and gender-based prevention interventions. J Acquir Immune Defic Syndr 2011,56:151-165.
  16. Menzies N, Abang B, Wanyenze R, Nuwaha F, Mugisha B, Coutinho A, et al. The costs and effectiveness of four HIV counseling and testing strategies in Uganda. AIDS 2009,23:395-401.
  17. Sweat M, Morin S, Celentano D, Mulawa M, Singh B, Mbwambo J, et al. Community-based intervention to increase HIV testing and case detection in people aged 16-32 years in Tanzania, Zimbabwe, and Thailand (NIMH Project Accept, HPTN 043): a randomised study. Lancet Infect Dis 2011,11:525-532.
  18. Mabuto T, Latka MH, Kuwane B, Churchyard GJ, Charalambous S, Hoffmann CJ. Four models of HIV counseling and testing: utilization and test results in South Africa. PLoS One 2014,9:e102267.
  19. Nordberg E, Holmberg S, Kiugu S. Exploring the interface between first and second level of care: referrals in rural Africa. Trop Med Int Health 1996,1:107-111.
  20. Atkinson S, Ngwengwe A, Macwan’gi M, Ngulube TJ, Harpham T, O’Connell A. The referral process and urban health care in sub-Saharan Africa: the case of Lusaka, Zambia. Soc Sci Med 1999,49:27-38.
  21. Hardon AP, Akurut D, Comoro C, Ekezie C, Irunde HF, Gerrits T, et al. Hunger, waiting time and transport costs: time to confront challenges to ART adherence in Africa. AIDS Care 2007,19:658-665.
  22. Macintyre K, Hotchkiss DR. Referral revisited: community financing schemes and emergency transport in rural Africa. Soc Sci Med 1999,49:1473-1487.
  23. Nsigaye R, Wringe A, Roura M, Kalluvya S, Urassa M, Busza J, et al. From HIV diagnosis to treatment: evaluation of a referral system to promote and monitor access to antiretroviral therapy in rural Tanzania. J Int AIDS Soc 2009,12:31.
  24. van Rooyen H, Barnabas RV, Baeten JM, Phakathi Z, Joseph P, Krows M, et al. High HIV testing uptake and linkage to care in a novel program of home-based HIV counseling and testing with facilitated referral in KwaZulu-Natal, South Africa. J Acquir Immune Defic Syndr 2013,64:e1-8.
  25. Bassett IV, Govindasamy D, Erlwanger AS, Hyle EP, Kranzer K, van Schaik N, et al. Mobile HIV screening in Cape Town, South Africa: clinical impact, cost and cost-effectiveness. PLoS One 2014,9:e85197.
  26. Team RC. R: A language and environment for statistical computing. In. Vienna, Austria: R Foundation for Statistical Computing; 2014.
  27. Laeyendecker O, Piwowar-Manning E, Fiamma A, Kulich M, Donnell D, Bassuk D, et al. Estimation of HIV incidence in a large, community-based, randomized clinical trial: NIMH project accept (HIV Prevention Trials Network 043). PLoS One 2013,8:e68349.
  28. Crist JD. Theory derivation and the telenovela: facilitating Mexican-American family use of home healthcare. Nurs Sci Q 2008,21:39-40.
  29. Vaughn S. Stroke and heart disease prevention education via telenovela: a focus group’s evaluation. Rehabil Nurs 2012,37:215-219.
  30. Myburgh H. The clinic as a gender space: masculinities, health seeking behavior and HIV & AIDS. Consult African Intel 2011:1-5.
  31. Vaughan PW, Rogers EM, Singhal A, Swalehe RM. Entertainment-education and HIV/AIDS prevention: a field experiment in Tanzania. J Health Commun 2000,5 Suppl:81-100.
  32. Wilkin HA, Valente TW, Murphy S, Cody MJ, Huang G, Beck V. Does entertainment-education work with Latinos in the United States? Identification and the effects of a telenovela breast cancer storyline. J Health Commun 2007,12:455-469.
  33. Young SD. Social media technologies for HIV prevention study retention among minority men who have sex with men (MSM). AIDS Behav 2014,18:1625-1629.
  34. Coates TJ, Kulich M, Celentano DD, Zelaya CE, Chariyalertsak S, Chingono A, et al. Effect of community-based voluntary counselling and testing on HIV incidence and social and behavioural outcomes (NIMH Project Accept; HPTN 043): a cluster-randomised trial. Lancet Glob Health 2014,2:e267-277.


Table I: Characteristics of testers by site  


n(% of N)



n(% of N)




n(% of N)


Female 23009 (56.51) 17707 (56.22) 40721 (56.38)
Male 17712 (43.49) 13792 (43.78) 31499 (43.62)
15-19 5658 (13.90) 6733 (21.37) 12391 (17.16)
20-29 22993 (56.47) 15777 (59.08) 38770 (53.68)
30-39 8169 (20.06) 5584 (17.72) 13753 (1904)
40-49 3896 (9.57) 3410 (10.82) 7306 (10.12)




Table II: HIV prevalence rates by sex, age

N = 2009

n(% of N)


N = 36840

n(% of N)

95% CI HIV-Positive

N = 1334

n(% of N)


N = 29296

n(% of N)

95% CI HIV-Positive

N = 3343

n(% of N)


N = 66136

n(% of N)

95% CI
15-19 79 (2.0) 3803 (98.0) 1.6, 2.5 69 (1.6) 4146 (98.4) 1.3, 2.1 148 (1.8) 7949 (98.2) 1.6, 2.1
20-29 679 (5.3) 12088 (94.7) 4.9, 5.7 381 (4.4) 8351 (95.6) 3.9, 4.8 1060 (4.9) 20439 (95.1) 4.6, 5.2
30-39 450 (13.0) 3022 (87.0) 11.9, 14.1 323 (12.3) 2310 (87.7) 11.1, 13.6 773 (12.7) 5332 (87.3) 11.8, 13.5
40-49 196 (10.6) 1654 (89.4) 9.2, 12.1 142 (8.5) 1533 (91.5) 7.2, 9.9 338 (9.6) 3187 (90.4) 8.6, 10.6
15-19 12 (0.8) 1531 (99.2) 0.4, 1.4 14 (0.6) 2344 (99.4) 0.3, 1.0 26 (0.7) 3875 (99.3) 0.4, 1.0
20-29 205 (2.2) 8985 (97.8) 1.9, 2.6 146 (2.2) 6456 (97.8) 1.9, 2.6 351 (2.2) 15441 (97.8) 2.0, 2.5
30-39 260 (6.1) 4033 (93.9) 5.4, 6.8 167 (6.0) 2610 (94.0) 5.2, 7.0 427 (6.0) 6643 (94.0) 5.5, 6.6
40-49 128 (6.9) 1724 (93.1) 5.8, 8.2 92 (5.6) 1546 (94.4) 4.6, 6.9 220 (6.3) 33270 (93.7) 5.5, 7.2
*Both men and women



Table III: HIV-positive cases by sex, age referred from site to LTC support program

Gauteng Limpopo Total
Female Male Female Male Female Male
15-19 37 3 28 4 65 7
20-29 257 90 159 57 416 147
30-39 135 85 130 72 265 157
40-49 71 51 97 59 168 110
Total 500 229 414 192 914 421



Table IV: Linkage to care rates by sex, age
  Female Male Female Male Female Male
N = 451/500* N = 191/229 N = 239/414 N = 93/192 N = 690/914 N = 284/421
n(% of N) n(% of N) n(% of N) n(% of N) n(% of N) n(% of N)
15-19 32/37  (86.49) 2/3  (66.67) 17/28  (60.71) 1/4  (25.00) 49/65  (75.38) 3/7  (42.86)
20-29 232/257 (90.27) 77/90 (85.56) 104/159 (65.41) 32/57 (56.14) 336/416  (80.77) 109/147  (74.15)
30-39 129/135 (95.56) 78/85 (91.76) 81/130 (62.31) 39/72 (54.17) 210/265 (79.25) 117/157 (74.52)
40-49 58/71 (81.69) 34/51 (66.67) 37/97 (38.14) 21/59 (35.59) 95/168 (56.55) 55/110 (50.00)
* Numerator is reported linked to care. Denominator is total testing HIV-positive in S-N who opted in to the LTC program.